lightning¶
lightning is a library for large-scale linear classification, regression and ranking in Python.
Highlights:
- follows the scikit-learn API conventions
- supports natively both dense and sparse data representations
- computationally demanding parts implemented in Cython
Solvers supported:
- primal coordinate descent
- dual coordinate descent (SDCA, Prox-SDCA)
- SGD, AdaGrad, SAG, SAGA, SVRG
- FISTA
Example¶
Example that shows how to learn a multiclass classifier with group lasso penalty on the News20 dataset (c.f., Blondel et al. 2013):
from sklearn.datasets import fetch_20newsgroups_vectorized
from lightning.classification import CDClassifier
# Load News20 dataset from scikit-learn.
bunch = fetch_20newsgroups_vectorized(subset="all")
X = bunch.data
y = bunch.target
# Set classifier options.
clf = CDClassifier(penalty="l1/l2",
loss="squared_hinge",
multiclass=True,
max_iter=20,
alpha=1e-4,
C=1.0 / X.shape[0],
tol=1e-3)
# Train the model.
clf.fit(X, y)
# Accuracy
print(clf.score(X, y))
# Percentage of selected features
print(clf.n_nonzero(percentage=True))
Dependencies¶
lightning needs Python >= 2.7, setuptools, Numpy >= 1.3, SciPy >= 0.7, scikit-learn >= 0.15 and a working C/C++ compiler.
To run the tests you will also need nose >= 0.10.
Installation¶
To install lightning from pip, type:
pip install https://github.com/scikit-learn-contrib/lightning/archive/master.zip
To install lightning from source, type:
git clone https://github.com/scikit-learn-contrib/lightning.git
cd lightning
python setup.py build
sudo python setup.py install